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Keynote Speakers

Prof. Min Chen

University of Oxford

Myths and Promises of Data Intelligence

In this talk, the speaker will examine the following myths:
(1) The problem of "Big Data" is due to too much data. (2) The "Big
Data" problem is a recent phenomenon. (3) Machine intelligence is the
only hope. (4) Visualization provides insight. (5) Data processing
inequity is ubiquitous. The speaker will draw evidence from a number of
research projects in which he was involved to explain why Visual
Analytics may offer a promise, and will discuss the potential role of
the cyberspace in supporting data intelligence.

Dr. Rafal Mantiuk

University of Cambridge

Towards perceptually realistic visual experience

Today's computer graphics techniques make it possible to create
imagery that is hardly distinguishable from photographs. However, a
photograph is clearly no match to an actual real-world scene. I argue
that the next big challenge is to achieve perceptual realism by
creating artificial imagery that would be hard to distinguish from
reality. This requires profound changes in the entire imaging
pipeline, from acquisition and rendering to display, with the strong
focus on visual perception.

The technical limitations of display technologies make it very hard to
deliver perceptually realistic images. However, we can get much closer
to that goal by a technique that involves optimization of perceptual
match between real-world visual content and the rendition of that
content on a display. Given the limitations of a display and a model
of visual system, we can render images which are the closest match to
the real-world experience. I will demonstrate such approach on an
example of modeling night vision, in which we can simulate night
vision or compensate for its limitations. The method can be used in
games, driving simulators, or as a compensation for displays used
under varying ambient light levels.